World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
14911
World Ranking
7763
National Ranking
131

Michael S. Lew publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Michael S. Lew sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 210 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Michael S. Lew D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Michael S. Lew sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Michael S. Lew is affiliated with Leiden University in the Netherlands. Their research spans primarily the field of Computer Science, with a particular focus on subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Global and Planetary Change, Biomedical Engineering, and Demography.

Their scholarly output includes numerous papers addressing topics within multimodal machine learning, domain adaptation and few-shot learning, and advanced techniques for image and video retrieval. Their published works cover a range of subjects such as video surveillance and tracking methods, human pose and action recognition, as well as image enhancement techniques.

Frequent collaborators in their research include Erwin M. Bakker, Nan Pu, Wei Chen, Yu Liu, and Guoqiang Xiao. These partnerships reflect a broad collaborative network across related areas of study.

Michael S. Lew has published extensively in various academic venues. Notable frequent publication outlets include arXiv (Cornell University), the International Journal of Multimedia Information Retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Multimedia, and Engineering Applications of Artificial Intelligence.

Key recent papers authored or co-authored by Michael S. Lew include:

  • Deep Learning for Instance Retrieval: A Survey, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • A Memorizing and Generalizing Framework for Lifelong Person Re-Identification, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • New Ideas and Trends in Deep Multimodal Content Understanding: A Review, 2020, Neurocomputing
  • Integrating information theory and adversarial learning for cross-modal retrieval, 2021, Pattern Recognition
  • Feature Estimations Based Correlation Distillation for Incremental Image Retrieval, 2021, IEEE Transactions on Multimedia

Main research topics covered by Michael S. Lew include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Image Enhancement Techniques

Best Publications

  • Content-based multimedia information retrieval: State of the art and challenges

    Michael S. Lew;Nicu Sebe;Chabane Djeraba;Ramesh Jain

  • Deep learning for visual understanding

    Yanming Guo;Yu Liu;Ard Oerlemans;Songyang Lao

  • The MIR flickr retrieval evaluation

    Mark J. Huiskes;Michael S. Lew

  • A review of semantic segmentation using deep neural networks

    Yanming Guo;Yu Liu;Theodoros Georgiou;Michael S. Lew

  • Authentic facial expression analysis

    N. Sebe;M. S. Lew;Y. Sun;I. Cohen

  • New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative

    Mark J. Huiskes;Bart Thomee;Michael S. Lew

  • Image and Video Retrieval

    Wee-Kheng Leow;Michael S. Lew;Tat-Seng Chua;Wei-Ying Ma

  • Principles of Visual Information Retrieval

    Michael S. Lew

  • Deep Learning for Instance Retrieval: A Survey

    Unknown

  • Emotion recognition using a Cauchy Naive Bayes classifier

    N. Sebe;M.S. Lew;I. Cohen;A. Garg

  • The state of the art in image and video retrieval

    Nicu Sebe;Michael S. Lew;Xiang Zhou;Thomas S. Huang

  • Image retrieval using wavelet-based salient points

    Qi Tian;Nicu Sebe;Michael S. Lew;Etienne Loupias

  • Next-generation Web searches for visual content

    M.S. Lew

  • Learning and feature selection in stereo matching

    M.S. Lew;T.S. Huang;Kam Wong

  • Learning a Recurrent Residual Fusion Network for Multimodal Matching

    Yu Liu;Yanming Guo;Erwin M. Bakker;Michael S. Lew

  • Evaluation of salient point techniques

    Nicu Sebe;Qi Tian;Etienne Loupias;Michael S. Lew

  • A survey of traditional and deep learning-based feature descriptors for high dimensional data in computer vision

    Theodoros Georgiou;Yu Liu;Wei Chen;Michael S. Lew

  • Comparing salient point detectors

    Nicu Sebe;Michael S. Lew

  • Toward improved ranking metrics

    N. Sebe;M.S. Lew;D.P. Huijsmans

  • CNN-RNN: a large-scale hierarchical image classification framework

    Yanming Guo;Yu Liu;Erwin M. Bakker;Yuanhao Guo

  • The distributed ASCI Supercomputer project

    Henri Bal;Raoul Bhoedjang;Rutger Hofman;Ceriel Jacobs

  • Authentic facial expression analysis

    N. Sebe;M.S. Lew;I. Cohen;Yafei Sun

  • Facial expression recognition from video sequences

    I. Cohen;N. Sebe;A. Garg;M.S. Lew

Frequent Co-Authors

Nicu Sebe
Nicu Sebe University of Trento
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Ira Cohen
Ira Cohen Hewlett-Packard (United States)
Qi Tian
Qi Tian Huawei Technologies (China)
Thomas Bäck
Thomas Bäck Leiden University
Vladimir Pavlovic
Vladimir Pavlovic Rutgers, The State University of New Jersey
Theo Gevers
Theo Gevers University of Amsterdam
Kin-Man Lam
Kin-Man Lam Hong Kong Polytechnic University
Tat-Seng Chua
Tat-Seng Chua National University of Singapore

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